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School of Physical and Chemical Sciences

Neutrino Detection with Machine Learning at DUNE

Research Group: PPRC
Full-time Project: yes

Funding

Discuss with supervisor and/or admissions tutor

Project Description

Improving neutrino reconstruction with machine learning at DUNE.  DUNE is a future long baseline neutrino oscillation experiment in the USA aiming to discover a matter-antimatter asymmetry in neutrino oscillations.  Working with a combination of simulated and prototype detector data you will develop the neutrino reconstruction at DUNE, ultimately increasing DUNE's sensitivity to CP-violation in neutrino oscillations.  There will also be the opportunity to participate in test beams at CERN or Fermilab if desired.  The project will involve algorithm development, simulation, data analysis and optionally hardware work.

 

Requirements

Knowledge of C++, Python and machine learning would be useful.

 

SPCS Academics: Abbey Waldron